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检索条件"任意字段=Brazilian Symposium on Computer Graphics and Image Processing"

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Instanced Rendering of Massive CAD Models Using Shape Matching

Instanced Rendering of Massive CAD Models Using Shape Matchi...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Paulo Ivson Waldemar Celes Pontifical Catholic Univ. of Rio de Janeiro - PUC-Rio Rio de Janeiro Brazil Comput. Sci. Dept. Pontifical Catholic Univ. of Rio de Janeiro - PUC-Rio Rio de Janeiro Brazil

ISBN: (纸本)9781479942572

We present an efficient approach to greatly reduce memory usage and to achieve high rendering performance for massive 3D CAD models. Our work is based on the observation that these models often contain many instances of the same geometries. Using a shape matching algorithm, we identify these instances and estimate the optimal affine transformation between them. The resulting sets of unique geometries only require a fraction of the memory used by the original 3D model. This compact representation can be rendered efficiently using hardware-accelerated geometry instancing. As another benefit, this allows for interactive rendering of highly dynamic scenes of up to a million moving objects. Our proposal assumes no knowledge about the scene, and thus can be applied to other kinds of massive 3D models with similar properties.

关键词： Geometry Solid modeling Three-dimensional displays Shape Design automation Rendering (computer graphics)

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A Fast Feature Tracking Algorithm for Visual Odometry and Mapping Based on RGB-D Sensors

A Fast Feature Tracking Algorithm for Visual Odometry and Ma...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Bruno Marques Ferreira da Silva Luiz Marcos Garcia Gonçalves Department of Computer Engineering and Automation Federal University of Rio Grande do Norte Natal Brazil

The recent introduction of low cost sensors such as the Kinect allows the design of real-time applications (i.e. for Robotics) that exploit novel capabilities. One such application is Visual Odometry, a fundamental module of any robotic platform that uses the synchronized color/depth streams captured by these devices to build a map representation of the environment at the same that the robot is localized within the map. Aiming to minimize error accumulation inherent to the process of robot localization, we design a visual feature tracker that works as the front-end of a Visual Odometry system for RGB-D sensors. Feature points are added to the tracker selectively based on pre-specified criteria such as the number of currently active points and their spatial distribution throughout the image. Our proposal is a tracking strategy that allows real-time camera pose computation (average of 24.847 ms per frame) despite the fact that no specialized hardware (such as modern GPUs) is employed. Experiments carried out on publicly available benchmark and datasets demonstrate the usefulness of the method, which achieved RMSE rates superior to the state-of-the-art RGB-D SLAM algorithm.

关键词： Visualization Cameras Feature extraction Simultaneous localization and mapping Three-dimensional displays

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3D Face Reconstruction from Video Using 3D Morphable Model and Silhouette

3D Face Reconstruction from Video Using 3D Morphable Model a...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Christian Baumberger Mauricio Reyes Mihai Constantinescu Radu Olariu Edilson De Aguiar Thiago Oliveira Santos University of Bern Switzerland Inselspital Switzerland Universidade Federal do Espirito Santo Vitoria ES BR

ISBN: (纸本)9781479942572

Capitalizing on the advances of 3D face reconstruction from computer graphics and computer vision, this work presents a system to enable precise and robust 3D facial reconstruction from video in order to improve current approaches for doctor-patient communication tools. The reconstructed face can be used for emulation of aesthetic procedures in 3D. The proposed 3D face reconstruction algorithm uses a statistical shape model as well as information from facial landmarks and silhouette to iteratively model the face of a subject moving the face from front to left. The presented 3D active shape model approach enables the spatio-temporal tracking of facial landmarks and pose estimation based on a few initial facial landmarks defined in the first frame. Silhouette information extracted from key frames allows for better face reconstruction. The proposed methods were rigorously evaluated with experiments using real and artificial data. Results showed that the proposed method can detect facial landmarks with an approximate median error of 5% intraocular distance, can estimate pose with a median error below 5 degrees, and that silhouette information can improve reconstruction accuracy in all facial regions, specially on the cheeks.

关键词： Shape Face Three-dimensional displays Estimation Solid modeling image reconstruction Cameras

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Semi-supervised Learning for Relevance Feedback on image Retrieval Tasks

Semi-supervised Learning for Relevance Feedback on Image Ret...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Daniel Carlos Guimarães Pedronette Rodrigo T. Calumby Ricardo da S. Torres State Univ. of Sao Paulo (UNESP) Brazil Recod Lab - Institute of Computing University of Campinas (UNICAMP) Campinas SP Brazil University of Feira de Santana (UEFS) Feira de Santana BA Brazil Recod Lab. - Inst. of Comput. Universidade Estadual de Campinas Campinas SP BR

ISBN: (纸本)9781479942572

Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts required by these methods tend to increase as well, demanding approaches for reducing the need of user interactions. In this context, this paper proposes a semi-supervised learning algorithm for relevance feedback to be used in image retrieval tasks. The proposed semi-supervised algorithm aims at using both supervised and unsupervised approaches simultaneously. While a supervised step is performed using the information collected from the user feedback, an unsupervised step exploits the intrinsic dataset structure, which is represented in terms of ranked lists of images. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture descriptors and different datasets. The proposed approach was also evaluated on multimodal retrieval tasks, considering visual and textual descriptors. Experimental results demonstrate the effectiveness of the proposed approach.

关键词： image retrieval Shape image color analysis Visualization Semisupervised learning Educational institutions Feature extraction

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Statistical Learning Approach for Robust Melanoma Screening

Statistical Learning Approach for Robust Melanoma Screening

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Michel Fornaciali Sandra Avila Micael Carvalho Eduardo Valle University of Campinas RECOD Lab - DCA/FEEC/UNICAMP Campinas SP Brazil

ISBN: (纸本)9781479942572

According to the American Cancer Society, one person dies of melanoma every 57 minutes, although it is the most curable type of cancer if detected early. Thus, computeraided diagnosis for melanoma screening has been a topic of active research. Much of the existing art is based on the Bag-of-Visual-Words (BoVW) model, combined with color and texture descriptors. However, recent advances in the BoVW model, as well as the evaluation of the importance of the many different factors affecting the BoVW model were yet to be explored, thus motivating our work. We show that a new approach for melanoma screening, based upon the state-of-the-art BossaNova descriptors, shows very promising results for screening, reaching an AUC of up to 93.7%. An important contribution of this work is an evaluation of the factors that affect the performance of the two-layered BoVW model. Our results show that the low-level layer has a major impact on the accuracy of the model, but that the codebook size on the mid-level layer is also important. Those results may guide future works on melanoma screening.

关键词： Malignant tumors Lesions Feature extraction Vectors image color analysis Support vector machines Skin

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Improved interventional X-ray appearance 13

Improved interventional X-ray appearance

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13th IEEE International symposium on Mixed and Augmented Reality, ISMAR 2014

作者： Wang, Xiang Schulte Zu Berge, Christian Demirci, Stefanie Fallavollita, Pascal Navab, Nassir Computer Aided Medical Procedures and Augmented Reality Technische Universität München Germany School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9781479961849

Depth cues are an essential part of navigation and device positioning tasks during clinical interventions. Yet, many minimally-invasive procedures, such as catheterizations, are usually performed under X-ray guidance only depicting a 2D projection of the anatomy, which lacks depth information. Previous attempts to integrate pre-operative 3D data of the patient by registering these to intra-operative data have led to virtual 3D renderings independent of the original X-ray appearance and planar 2D color overlays (e.g. roadmaps). A major drawback associated to these solutions is the trade-off between X-ray attenuation values that is completely neglected during 3D renderings, and depth perception not being incorporated into the 2D roadmaps. This paper presents a novel technique for enhancing depth perception of interventional X-ray images preserving the original attenuation appearance. Starting from patient-specific pre-operative 3D data, our method relies on GPU ray casting to compute a colored depth map, which assigns a predefined color to the first incidence of gradient magnitude value above a predefined threshold along the ray. The colored depth map values are carefully integrated into the X-Ray image while maintaining its original grey-scale intensities. The presented method was tested and analysed for three relevant clinical scenarios covering different anatomical aspects and targeting different levels of interventional expertise. Results demonstrate that improving depth perception of X-ray images has the potential to lead to safer and more efficient clinical interventions. © 2014 IEEE.

关键词： graphics processing unit

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Pre-alignment for Co-registration in Native Space

Pre-alignment for Co-registration in Native Space

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Wu Shin Ting Augusto Cavalcante Valente Lionis de Souza Watanabe Clarissa Lin Yasuda Ana Carolina Coan Fernando Cendes Universidade Estadual de Campinas Campinas SP BR University of Campinas SP Brazil

For nonlesional patients, the correct localization of the epileptogenic foci in native space remains a great challenge. Non-invasive functional PET images that provide information about cerebral activities may reveal the origin of seizure activity, but without precise anatomical detail. Co-registration of the functional images with MR images on the basis of maximization of mutual information (MMI) has shown to be very promising in improving presurgical evaluation. Nevertheless, a mutual information (MI) function is non-convex and the convergence of an algorithm to its optimum is guaranteed only if the initial estimate lies in its convex vicinity. We present in this paper a generally applicable method that pre-aligns the DICOM images such that their relative position becomes close to an optimum. The key to our solution is a robust user-guided interactive procedure to extract valid voxels, for both the centroid estimation and the registration. Aiming at comparative analysis, we introduce a numerical condition to quantify registration errors. The results are acceptable when we consider the intrinsic problems of the MMI-based registration algorithm we implemented.

关键词： Computed tomography graphics processing units Single photon emission computed tomography Positron emission tomography DICOM Noise Hospitals

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Parallel Shortest Path Algorithm for Voronoi Diagrams with Generalized Distance Functions

Parallel Shortest Path Algorithm for Voronoi Diagrams with G...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Julio Toss João Luiz Dihl Comba Bruno Raffin UFRGS Federal University of Rio Grande do Sul Porto Alegre RS Brazil Inria CNRS Univ. Grenoble Alpes Grenoble France

Voronoi diagrams are fundamental data structures in computational geometry with applications on different areas. Recent soft object simulation algorithms for real time physics engines require the computation of Voronoi diagrams over 3D images with non-Euclidean distances. In this case, the computation must be performed over a graph, where the edges encode the required distance information. But excessive computation time of Voronoi diagrams prevent more sophisticated deformations that require interactive topological changes, such as cutting or stitching used in virtual surgery simulations. The major bottleneck in the Voronoi computation in this case is a shortest-path algorithm that must be computed multiple times during the deformation. In this paper, we tackle this problem by proposing a GPU algorithm of the shortest-path algorithm from multiple sources using generalized distance functions. Our algorithm was designed to leverage the grid-based nature of the underlying graph used in the simulation. Experimental results report speed-ups up to 65× over a current reference sequential method.

关键词： graphics processing units Materials Computational modeling Indexes Algorithm design and analysis Topology Instruction sets

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Real-Time Fine-Tuned Adjustment of Fiber Tracking Parameters

Real-Time Fine-Tuned Adjustment of Fiber Tracking Parameters

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Annual IEEE symposium on computer-Based Medical Systems

作者： Adiel Mittmann Eros Comunello Aldo von Wangenheim Image Processing and Computer Graphics Lab-LAPIX Federal University of Santa Catarina-UFSC Florianopolis SC Brazil

Fiber tracking is a mature technique that aids neurosurgeons by providing the location of neuronal fibers in a patient's brain. Although the interactivity of tools have been typically limited, the exploitation of the parallel nature of fiber tracking is rapidly changing this landscape. The parallel environment offered by GPUs and modern CPUs enables fiber tracking to be executed very quickly on consumer-grade computers. The adjustment of fiber tracking parameters can currently be made on the fly, and the new results can be both computed and displayed in real-time on the screen. In order to further improve the interactivity of fiber tracking tools, this article proposes the application of histogram equalization, a traditional digital image processing procedure, to the fiber tracking parameters. The non-linear scale obtained by this process allows the user to interactively explore sensitive regions of the parameter space. Results show that this scale can be computed in real-time and that it can be cleanly integrated into fiber tracking tools.

关键词： Histograms Trajectory Indexes Visualization graphics processing units Real-time systems Anisotropic magnetoresistance

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Superpixel-Based Interactive Classification of Very High Resolution images

Superpixel-Based Interactive Classification of Very High Res...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： John E. Vargas Priscila T. M. Saito Alexandre X. Falcao Pedro J. De Rezende Jefersson A. Dos Santos Institute of Computing University of Campinas Campinas Brazil Federal Technological University of Parana Cornelio Procopio Brazil Inst. of Comput. Universidade Estadual de Campinas Campinas SP BR Universidade Federal de Minas Gerais Belo Horizonte MG BR

ISBN: (纸本)9781479942572

Very high resolution (VHR) images are large datasets for pixel annotation -- a process that has depended on the supervised training of an effective pixel classifier. Active learning techniques have mitigated this problem, but pixel descriptors are limited to local image information and the large number of pixels makes the response time to the user's actions impractical, during active learning. To circumvent the problem, we present an active learning strategy that relies on superpixel descriptors and a priori dataset reduction. Firstly, we compare VHR image annotation using superpixel- and pixel-based classifiers, as designed by the same state-of-the-art active learning technique -- Multi-Class Level Uncertainty (MCLU). Even with the dataset reduction provided by the superpixel representation, MCLU remains unfeasible for user interaction. Therefore, we propose a technique to considerably reduce the superpixel dataset for active learning. Moreover, we subdivide the reduced dataset into a list of subsets with random sample rearrangement to gain both speed and sample diversity during the active learning process.

关键词： Training Uncertainty image color analysis Accuracy Clustering algorithms Support vector machines Histograms

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